“Moreover, the potential of AI to predict mortality based on heart measurements highlights its potential to revolutionise cardiac care and improve patient prognosis.”
The researchers say future studies should test the model using larger groups of patients from different hospitals, with various types of MRI scanners, and including other common diseases seen in medical practice to see if it works well in a broader range of real-world situations.
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Other recent research from the teams at UEA, Leeds and Sheffield has refined the method of using heart MRI scans for female patients, particularly for those with early or borderline heart disease, which meant that 16.5pc more females were able to be diagnosed.
The research was a collaboration between the University of East Anglia, the University of Leeds, the University of Sheffield, Leiden University Medical Centre, the Norfolk and Norwich University Hospitals NHS Foundation Trust, Sheffield Teaching Hospitals NHS Foundation Trust and Leeds Teaching Hospitals NHS Trust.
The study was supported by funding for Dr Pankaj Garg from the Wellcome Trust Clinical Research Career Development Fellowship.
'Development and validation of AI-derived segmentation of four-chamber cine CMR' is published in the European Radiology Experimental.
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